Integro-differential Models with a K-symmetric Operator for Controlling Unmanned Aerial Vehicles Using a Improved Gradient Method

Dakhno, Nataliia; Барабаш, Олег; Shevchenko, Halyna; Leshchenko, Olga; Dudnik, Andriy

doi:10.1109/apuavd53804.2021.9615431

Cited by 7 publications

(2 citation statements)

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“…As a result of research conducted by Ukrainian scientists, new methods for numerical solution of integrodifferential equations have been proposed. The main advantage is the reduction of computational costs in solving dynamic models for remote control of unmanned aerial vehicles expressed through integro-differential equations with K-positive defined K-symmetric operators based on the improvement and application of the theory of variational gradient methods to these equations [17,18].…”

Section: Analysis Of the Latest Research And Publicationsmentioning

confidence: 99%

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Development of Control Laws of Unmanned Aerial Vehicles for Performing Group Flight at the Straight-Line Horizontal Flight Stage

Barabash,

Kyrianov

2023

A.I.S.

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The article proposes an improved approach to controlling groups of unmanned aerial vehicles (UAVs) aimed at increasing the overall efficiency and flexibility of the control process. The use of a heterogeneous external field, which varies both in magnitude and direction, allows achieving greater adaptability and accuracy in controlling a group of UAVs. A vector field for unmanned aerial vehicles determines the direction and intensity of the vehicles' movement in space. Such vector fields can be used to develop UAV control laws, including determining optimal flight paths, controlling speed, avoiding obstacles, and ensuring coordination of a group of UAVs. The subject of the study is the methods of controlling groups of autonomous UAVs, where each vehicle may have different speeds and flight directions. To solve this problem, various methods of using a heterogeneous field have been developed and proposed. Instead of using a homogeneous field that provides a constant flight speed, a vector field is used that adapts to different conditions and characteristics of the vehicles in the group. This method allows for effective group management, ensuring the necessary coordination and interaction between the vehicles. An analysis of recent research and publications in the field of autonomous system control indicates the feasibility of using machine learning, vector fields, and a large amount of data to successfully coordinate the movement of autonomous systems. These approaches make it possible to create efficient and reliable control systems. The aim of the study is to develop laws for controlling the movement of a group of autonomous unmanned aerial vehicles at the stage of straight-line horizontal flight based on natural analogues to improve the efficiency and reliability of their coordinated movement in different conditions. The main conclusions of the research are that the proposed method of controlling groups of UAVs based on a heterogeneous field can be implemented. It takes into account a variety of vehicle characteristics and environmental conditions that are typical for real-world use scenarios. This work opens up prospects for further improving the management of UAV groups and their use in various fields of activity. The article emphasises the relevance of technology development for autonomous unmanned systems, especially in the context of autonomous transport systems.

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Section: Analysis Of the Latest Research And Publicationsmentioning

confidence: 99%

“…From the above, we conclude that ( ) ( ) ends inside the region, is defined as where  is a bounded constant whose value depends on the initial positions of the devices, the parameters of the final path, the tuning coefficients and the characteristics of the devices themselves [17].…”

Section:  mentioning

confidence: 99%